As a commercial vessel embarks on a voyage from Saudi Arabia’s Ras Tanura to Tokyo Bay, it’s not simply a carrier of goods. This ship is a conduit for a vast sea of data, channeled among an intricate web of stakeholders and sophisticated technological frameworks.
Take Maersk as a prime example. This titan in container shipping and logistics boasts a global workforce exceeding 100,000, a presence in 120 nations, and a fleet of roughly 800 container vessels, each with the capacity to haul 18,000 tractor-trailer-sized containers. The journey of the contents within these mammoth metal boxes—from creation to delivery—is chronicled by hundreds, or even thousands, of data points, underscoring the sheer volume of supply chain data that corporations juggle daily.
Traditionally, accessing the lion’s share of an organization’s supply chain data has been the remit of experts, spread across a myriad of disparate data systems. Shackled by the constraints of conventional data warehouses and their demanding requirements for maintenance, oversight, and financial investment, a wealth of data generated by today’s increasingly digitalized supply chains has been rendered dormant within data lakes, unexploited by the businesses they serve.
A recent survey by Boston Consulting Group in 2023 indicates that 56% of executives acknowledge that despite ongoing investments in modern data frameworks, the cost of managing data operations continues to be a significant hurdle. The consultancy also projects the challenge to intensify, with the global data volume expected to burgeon at a 21% rate from 2021 to 2024, reaching a staggering 149 zettabytes.
Data is everywhere,
observes Mark Sear, Maersk’s director of AI, data, and integration. He illustrates the data-rich odyssey of a simple product, like a computer mouse, traveling from China to the United Kingdom. Every leg of its journey—from the factory floor to the consumer’s doorstep—is punctuated by a myriad of data points.
Sear suggests that organizations poised to weave these extensive data tapestries into their operations stand to gain immeasurable business advantages. Each data point represents a chance for enhancement—to boost profitability, expand knowledge, refine pricing strategies, optimize staffing, and fulfill customer expectations,
he asserts.
Companies like Maersk are gravitating towards an innovative architectural solution: the data lakehouse. This hybrid model merges the expansive, cost-efficient nature of a data lake with the capabilities and robust performance of a data warehouse. The data lakehouse model aspires to amalgamate fragmented supply chain data and democratize access, embracing structured, semi-structured, and unstructured data alike. By anchoring analytics atop the lakehouse, this emergent framework aims to propel supply chain efficiency forward, delivering enhanced performance, governance, and the potential to facilitate immediate data analysis while curbing operational expenses.
